Define best practices for model development, MLOps, code reviews, and testing.
Collaborate with product managers to translate business goals (e.g., match quality, latency) into technical specifications.
Drive architectural decisions for AI services (inference pipelines, embedding stores, LLM orchestration).
Conduct regular design reviews and ensure technical documentation.
Design and fine-tune transformer-based models for resume/job description understanding.
Build and optimize vector search pipelines for semantic candidate matching.
Develop agentic workflows using LLMs (GPT-4, Claude, Gemini) for screening, interview scheduling, and feedback synthesis.
Implement production RAG systems with low latency.
Build data pipelines for feature extraction, embedding generation, and model evaluation.
Monitor model performance, drift, and retraining triggers.
Work closely with backend engineers to deploy models via REST APIs (FastAPI, TorchServe, or similar).
Partner with data engineers to ensure high-quality training data from hiring interactions.
Coordinate with product & design to embed AI features seamlessly into UX.
Ensure compliance with data privacy (GDPR, CCPA) and fairness/anti-bias standards.

7+ years of software engineering experience, with 5+ years in a tech lead or senior mentorship role.
Strong proficiency and experience with ML frameworks: PyTorch or TensorFlow.
Deep knowledge of NLP and working with text data at scale.
Proven experience deploying LLMs or embedding models to production.
Experience with vector databases.
Strong understanding of retrieval, ranking, and relevance metrics (NDCG, MRR, Recall@K).
Familiarity with prompt engineering, chain-of-thought, and agent frameworks.
Experience with MLOps tools.
Excellent communication skills: ability to explain complex AI concepts to non-technical stakeholders.
Experience conducting code reviews, running agile ceremonies, and unblocking team members.
A bias for action and pragmatic trade-offs (speed vs. accuracy vs. cost).
Nice to have: Experience in recruiting, HR tech, or marketplace platforms, etc.
Background in graph ML or recommendation systems.
Contributions to open-source AI projects or papers at conferences (NeurIPS, ACL, RecSys).
Experience with cloud infrastructure (AWS EKS, Lambda, S3, RDS) and infrastructure-as-code (Terraform).
Knowledge of model fairness, bias detection, and explainability (SHAP, LIME).

JobHire is mission-driven, fast-growing, and profitable global company.
Amazing opportunity to scale-up business growth, improving people’s careers and lives.
Brilliant team of the strongest A players from McKinsey, Nexters, Gett, Glovo.
Competitive salary + equity in a fast-growing AI startup.
Remote-first culture with flexible hours.
Opportunity to shape the AI roadmap from day one.

AI Engineering Tech Lead

Key skills